package cn.doitedu.day02

import org.apache.spark.rdd.RDD
import org.apache.spark.{HashPartitioner, SparkConf, SparkContext}

object T23_PartitionByDemo {

  def main(args: Array[String]): Unit = {

    //1.创建SparkConf
    val conf = new SparkConf().setAppName("MapPartitionsWithIndexDemo")
      .setMaster("local[4]")
    //2.创建SparkContext
    val sc = new SparkContext(conf)

    val lst: Seq[(String, Int)] = List(
      ("spark", 1), ("hadoop", 1), ("hive", 1), ("spark", 1),
      ("spark", 1), ("flink", 1), ("hbase", 1), ("spark", 1),
      ("kafka", 1), ("kafka", 1), ("kafka", 1), ("kafka", 1),
      ("hadoop", 1), ("flink", 1), ("hive", 1), ("flink", 1)
    )
    //通过并行化的方式创建RDD，分区数量为4
    val wordAndOne: RDD[(String, Int)] = sc.parallelize(lst, 4)

    val partitioner = new HashPartitioner(wordAndOne.partitions.length)
    val partitioned = wordAndOne.partitionBy(partitioner)
    partitioned.saveAsTextFile("out/out18")

  }

}
